基于支持向量回归的PM浓度实时预报

被引:17
作者
朱亚杰
李琦
侯俊雄
冯逍
范竣翔
机构
[1] 北京大学地球与空间科学学院遥感与地理信息系统研究所
关键词
支持向量回归; 空气质量; PM2.5浓度预报;
D O I
暂无
中图分类号
X513 [粒状污染物];
学科分类号
0706 ; 070602 ;
摘要
为了研究适合于我国当前重污染天气的实时空气质量预报模型,论文利用支持向量回归方法对北京市地面空气质量监测数据和气象数据进行分析,构建了基于支持向量回归的PM2.5浓度实时预报模型。实验表明,该方法能够对未来6日内的日均PM2.5浓度以及未来0~72h内的小时级PM2.5浓度进行预报,且模型训练过程和预报过程都耗时很短,适用于建立PM2.5浓度实时预报系统。
引用
收藏
页码:12 / 17+22 +22
页数:7
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